Reputation: 2928
I realise that MongoDB, by it's very nature, doesn't and probably never will support these kinds of transactions. However, I have found that I do need to use them in a somewhat limited fashion, so I've come up with the following solution, and I'm wondering: is this the best way of doing it, and can it be improved upon? (before I go and implement it in my app!)
Obviously the transaction is controlled via the application (in my case, a Python web app). For each document in this transaction (in any collection), the following fields are added:
'lock_status': bool (true = locked, false = unlocked),
'data_old': dict (of any old values - current values really - that are being changed),
'data_new': dict (of values replacing the old (current) values - should be an identical list to data_old),
'change_complete': bool (true = the update to this specific document has occurred and was successful),
'transaction_id': ObjectId of the parent transaction
In addition, there is a transaction
collection which stores documents detailing each transaction in progress. They look like:
{
'_id': ObjectId,
'date_added': datetime,
'status': bool (true = all changes successful, false = in progress),
'collections': array of collection names involved in the transaction
}
And here's the logic of the process. Hopefully it works in such a way that if it's interupted, or fails in some other way, it can be rolled back properly.
1: Set up a transaction
document
2: For each document that is affected by this transaction:
lock_status
to true
(to 'lock' the document from being modified)data_old
and data_new
to their old and new valueschange_complete
to false
transaction_id
to the ObjectId of the transaction
document we just made3: Perform the update. For each document affected:
data_new
valueschange_complete
to true
4: Set the transaction
document's status
to true
(as all data has been modified successfully)
5: For each document affected by the transaction, do some clean up:
data_old
and data_new
, as they're no longer neededlock_status
to false
(to unlock the document)6: Remove the transaction
document set up in step 1 (or as suggested, mark it as complete)
I think that logically works in such a way that if it fails at any point, all data can be either rolled back or the transaction can be continued (depending on what you want to do). Obviously all rollback/recovery/etc. is performed by the application and not the database, by using the transaction
documents and the documents in the other collections with that transaction_id.
Is there any glaring error in this logic that I've missed or overlooked? Is there a more efficient way of going about it (e.g. less writing/reading from the database)?
Upvotes: 23
Views: 20234
Reputation: 10069
MongoDB 4.0 adds support for multi-document ACID transactions.
Java Example:
try (ClientSession clientSession = client.startSession()) {
clientSession.startTransaction();
collection.insertOne(clientSession, docOne);
collection.insertOne(clientSession, docTwo);
clientSession.commitTransaction();
}
Note, it works for replica set. You can still have a replica set with one node and run it on local machine.
Upvotes: 6
Reputation: 2374
MongoDB 4.0 is adding (multi-collection) multi-document transactions: link
Upvotes: 1
Reputation: 30481
As a generic response multi-document commits on MongoDB can be performed as two phase commits, which have been somewhat extensively documented in the manual (See: http://docs.mongodb.org/manual/tutorial/perform-two-phase-commits/).
The pattern suggested by the manual is briefly to following:
transactions
collection, that includes target document, source document, value and state (of the transaction)initial
as the state
state
to pending
committed
done
In addition:
state
value canceling
Some specific notes for your implementation:
lock_status
, data_old
, data_new
into source/target documents. These should be properties of the transactions, not the documents themselves. DBref
s: http://www.mongodb.org/display/DOCS/Database+Referencesdone
seems like a better idea since this allows you to later debug and find out what kind of transactions have been performed. I'm pretty sure you won't run out of disk space either (and for this there are solutions as well).Upvotes: 13